1. Technical Field
Present invention embodiments relate to context accumulation, and more specifically, to determining data associated with the same entity based on properties or behaviors of entity features.
2. Discussion of the Related Art
Entity resolution may be used to determine data associated with the same entity (e.g., person, animal, business, object, etc.). For example, two or more customer records may contain slightly different data (e.g., first names of Bill and William), but still be associated with the same person or entity. An entity may include various features or characteristics (e.g., name, address, date of birth, etc.). The entity features may be used to determine a confidence or score indicating a degree of certainty that different data records are associated with the same entity.
Entity resolution may be utilized within a single data source or across plural data sources to identify duplicate data records and/or associate data records with a common entity. Systems performing entity resolution and relationship discovery use feature-specific rules. In these types of systems, a series of new rules is introduced in response to adding a new identifying feature for an entity. For example, after a new identifying feature pertaining to loyalty club number is added for a person entity, a skilled user introduces a series of new rules indicating the manner in which the new loyalty card number feature is weighed for entity resolution (in conjunction with other entity features). However, the quantity of new rules for these systems rapidly becomes unmanageable as additional entity types (e.g., person, animal, business, object, etc.) and features are introduced.